During the last few decades, interest in radio technologies for providing services for voice, video, data and the like has surged. Cellular communications service, for example, has provided voice and text messaging services to many millions of people worldwide. Satellite radio services have also introduced radio communications to areas which are not well served by cellular operators and also provide large scale broadcast service even to areas that are well covered by cellular networks, e.g., as provided by companies such as Sirius and XM.
When radio signals are transmitted over an air interface via a radio channel toward one or more receivers, e.g., by a cellular base station or a satellite, those radio signals are affected by the characteristics of that channel. Some sort of correction process, or a number of correction processes, can be applied to ensure, or attempt to ensure, that the signal which is received is decoded to recover the information that was actually transmitted. Broadcast radio presents a particular challenge in this regard because some of the processes which are typically used in cellular systems to correct erroneously received signals, e.g., retransmission based on feedback from the receiver, are not easily adapted to broadcast systems wherein any number of receivers in any number of locations may tune in and out of particular broadcasts somewhat rapidly. Accordingly, diversity reception, wherein a receiver uses information from multiple radio paths to reconstruct a transmitted signal, can be used to aid in error correction in such systems.
An equalization process is also commonly performed to offset the effects of the channel as part of the decoding process of the received signal(s). When a signal is received in a diversity receiver via two paths of relative delay L symbols, an equalizer using the Viterbi Maximum Likelihood Sequence Estimation (MLSE) procedure is an optimum decoder, but the complexity of the procedure is the order of ML, where M is the size of the symbol alphabet. This complexity is excessive when the relative path delay L is a large number of symbols, in the sense that the equalization process consumes too much of the processing bandwidth which is available to the receiver when the relative delay L is a large number of symbols. Since the receivers in, for example, satellite radio systems, are essentially at unknown locations relative to their respective transmitters, it is not possible to synchronize the reception of the various radio paths which they receive and, accordingly, it is possible for such receivers to experience relative path delays L on the order of, e.g., +/−5 msec or thousands of symbol periods, which renders MLSE equalizers prohibitively computationally expensive.
A form of equalizer known as a decimating equalizer can alternatively be used, wherein signal samples i, i+L, i+2L, i+3L etc are processed by an instance i of the MLSE equalizer to decode symbols i, i+L, i+2L and so forth. Using L such equalizers, each processing 1/Lth of the samples, a receiver can thus decode all symbols. The complexity of the decimating equalizer is only of the order of M per decoded symbol, which is much lower than ML. However, the decimating equalizer only works when the relative path delay is close to an integer number L of symbol periods.
There is therefore a need for a receiver equalizer that can decode signals when the second path is delayed by, for example, a large, non-integer number of symbol periods.